The measurement of physiological signals is difficult because the underlying physiological processes generate very low level signals and interfering noise is inherent in the body and the interface between the body and sensors of the physiological processes. For example, the measurement of electrocardiogram (ECG) signals is based on the electrical activity generated by the electrical depolarization of the heart muscle. The signals are typically detected by surface electrodes mounted on the chest of the patient. The signals are initially weak at the signal source (i.e., the heart) and are even weaker at the surface of the chest. Furthermore, electrical interference from the activity of other muscles, noise caused by patient breathing, general movement, and the like cause additional interference with the ECG signal. External electrical interference, such as 60 Hertz (Hz) interference, also compounds the ECG measurement problem. Therefore, great care must be taken in the design and use of physiological processors to enhance the quality of the desired signal and reduce the effects of interfering signals.
Another common physiological measurement that is made difficult by the presence of interfering noise is the measure of oxygen saturation in the blood. This measurement is frequently performed with a pulse oximeter 1, illustrated in the functional block diagram of FIG. 1. A transmissive pulse oximetry sensor 2 is placed on a finger 4 of the patient. First and second light sources 6 and 8 are directed through the fleshy portion of the finger 4 and detected by one or more light detectors 10 on the opposite side of the finger. As is well known in the art, the light from light sources 6 and 8 are of different wavelengths that are differentially absorbed by oxygenated blood cells. The first light source 6 is typically designated as a Red light source having a wavelength in the red region of the spectrum. The second light source 8 is typically designated the IR source having a wavelength in the near infrared region of the spectrum.
The pulse oximeter 1 determines the oxygen saturation based on a ratio of the light detected from the Red light source 6 and the IR light source 8, respectively. A ratio calculator 12 determines the ratio of detected light and uses the value of the ratio as an index to a look-up table 14. The look-up table 14 contains data relating the ratio of detected light to the oxygen saturation in the blood. A typical oxygen saturation curve 18 is illustrated in FIG. 2 where the percentage of oxygen saturation is plotted against the ratio of detected light from the Red light source 6 and the IR light source 8 (see FIG. 1). Pulse oximeters may also use reflective pulse oximetry sensors (not shown) in which the light sources and light detectors are positioned adjacent each other, and the light from the light sources is reflected back to the detector(s) by oxygenated blood cells in the finger 4.
The measurement of blood oxygen saturation is important for physicians who are monitoring a patient during surgery and at other times. As with other physiological measurements, pulse oximetry measurement also is susceptible to interference from noise. As is known in the art, pulse oximetry is particularly susceptible to interference from stray light and from patient motion. Stray light detected by the light detector 10 can cause erroneous calculation of the ratio. Known techniques are employed to reduce the interference caused by stray light. The interference from patient motion is a much more difficult noise source and is the subject of intensive research.
Therefore, it can be appreciated that there is a significant need for a system and method for measurement of physiological signals that enhances the desired signal in the presence of interfering noise signals. This and other advantages provided by the present invention are described in the detailed description and accompanying figures.